Description Usage Arguments Details Value References Examples
This function uses Bayesian mixed models to estimate individual effect sizes and to test theoretical order constraints.
1 2 3 4 5 6 7 8 9 10 11 12 | constraintBF(
formula,
data,
whichRandom,
ID,
whichConstraint,
rscaleEffects,
iterationsPosterior = 10000,
iterationsPrior = iterationsPosterior * 10,
burnin = 1000,
...
)
|
formula |
a formula containing the full model. |
data |
a |
whichRandom |
a character vector specifying which factors are random. |
ID |
a character vector of length one specifying which variable holds the subject ID. |
whichConstraint |
a named character vector specifying the constraints placed on certain factors; see Details. |
rscaleEffects |
a named vector of prior settings for individual factors. Values are scales, names are factor names; see Details. |
iterationsPosterior |
the number of iterations to sample from the posterior of the full model. |
iterationsPrior |
the number of iterations to sample from the prior of the full model. |
burnin |
the number of initial iterations to discard from posterior sampling. |
... |
further arguments to be passed to
|
This function provides a way of testing whether theoretical constraints on
certain effects hold for all subjects. The backend is provided by the
generalTestBF
function from the
BayesFactor-package
. The input formula is the
full model to be tested. It usually contains an interaction term between
the subject ID and the effect for which constraints are tested (e.g.
ID:condition
). The ID variable is to be specified in ID
and is
usually a random factor to be specified in whichRandom
.
Order constraints on effects should be specified in whichConstraint
,
as a named character vector. Each constraint in the vector can take 2 levels
of the effect. They are of the form:
"effect name" = "condition A" < "condition B"
. In order to impute more
than 2 levels, the same effect name has to be entered with different conditions
as the value. For instance, for testing whether conditions A < B < C, the
input should be: "effect name" = "condition A" < "condition B", "effect name" = "condition B" < "condition C"
.
At this point, constraints can only be tested for the same effect.
Priors have to be specified for all factors in whichConstraint
,
for ID
, and for the interaction between the two. A Detailed description
of the models, priors and methods is given in the documentation of
anovaBF
and more extensively in Rouder et al. (2012).
An object of class BFBayesFactorConstraint-class
.
Rouder, J. N., Morey, R. D., Speckman, P. L., Province, J. M., (2012) Default Bayes Factors for ANOVA Designs. Journal of Mathematical Psychology. 56. p. 356-374.
1 2 3 4 5 6 7 8 |
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